At Microsoft Frontier in Paris with @satyanadella, Eiffel Tower in the backdrop. My takeaway so far: the model is the easy part. Context, harness, access and trust are where the real work is. #AI
Update Sept 11, 2026:
Today, CMI shares in the excitement of the global mathematical community as we contemplate the announcement that the Navier-Stokes problem has apparently been settled.
claymath.org/news/navier-sto…
21/
Until someone answers that, we can't say what was actually won this month.
Your turn: which problem goes on Millennium 2 — and what's your argument that a swarm of agents can't touch it?
Bonus round: which of my seven falls first?
20/
Worse: a list designed to resist machines is a benchmark wearing a prize costume. It gets optimized against on day one.
So maybe the successor isn't a list of conjectures at all. Maybe it's a criterion:
What distinguishes a 166-page Lean certificate from math understanding?
🤖 Made with AI
19/
Now the honest limits.
If seven problems fall in months, the prize format is dead, and a sequel is a category error.
Clay's stated goal was to show the public that the frontier is open. A list that saturates in a year demonstrates the opposite.
18/ BQP ≠ BPP — why it resists
An unconditional separation would imply P ≠ PSPACE — itself wide open, and harder than anything on the original list.
You inherit complexity theory's deepest barrier as a prerequisite.
17/ BQP ≠ BPP
What it is: Prove that quantum computers are genuinely more powerful than classical ones.
Why it matters: We've built an industry on assuming it. It has never been proven.
🤖 Made with AI
16/ CH — why it resists
The hard part is deciding what would count as an answer at all.
Zero sensitivity to compute. You cannot brute-force a question about which axioms we ought to adopt.
15/ The Status of the Continuum Hypothesis
What it is: Is there a size of infinity sitting between the counting numbers and the real numbers?
Why it matters: Gödel and Cohen proved our axioms can't answer it. Woodin asks whether there's a right answer anyway.
🤖 Made with AI
14/ One-way functions — why it resists
Same meta-complexity barriers as P vs NP, plus a harder demand: average-case hardness, not worst-case.
Strictly less tractable than the problem everyone already calls intractable.
13/ Do One-Way Functions Exist?
What it is: Functions that are easy to compute and infeasible to reverse. Locks without keys.
Why it matters: All modern cryptography assumes they exist. It's strictly stronger than P ≠ NP — proving P ≠ NP would not save RSA.
🤖 Made with AI
12/ Standard Model QFT — why it resists
Physics constrains what counts as the right answer.
There's no formal oracle to confirm you built the right object. Only a community of physicists saying "yes, that's the thing we meant."
11/ Constructive QFT for the Standard Model
What it is: Build the mathematics of the actual theory of particle physics, rigorously, in four dimensions.
Why it matters: Yang-Mills was the warm-up. The full theory — matter, renormalization — is what physics actually runs on.
🤖 Made with AI
10/ Turbulence — why it resists
The statement isn't well-posed yet. Someone has to decide what "turbulence" formally means before anything can be proved.
That decision is the work. And it's exactly what a system optimized to close proofs won't do for you.
9/ A Rigorous Theory of Turbulence
What it is: Derive the observed statistical laws of turbulent flow — Kolmogorov's scaling — from the Navier-Stokes equations themselves
Why it matters: Turbulence is the last unsolved pbl of classical physics. We model it. We don't understand it
🤖 Made with AI
8/ Standard Conjectures — why it resists
The expected deliverable is a conceptual framework, not a derivation.
Search finds proofs inside an ontology. It does not invent the ontology.













